Mock Exam 2025

Advanced Financial Data Analytics

Download Solutions PDF

Mock Exam Access

To access the mock exam environment on Posit Cloud, click here: Mock Exam Workspace

This link will take you to the mock exam workspace where you can practice under conditions similar to the actual examination.

Exam Environment Instructions

This mock exam is designed to simulate the environment and format of your actual examination. Please read the following instructions carefully to understand how the exam will be administered:

Accessing Your Personalised Exam

  1. At the start of the examination period, you will be provided with a specific URL link in the official exam paper on Canvas.

  2. Clicking this link will take you to the designated exam workspace on Posit Cloud. This is a separate workspace specifically created for the examination.

  3. Important: When you click the link, the system will automatically create a personalised copy of the exam template for you. This will contain all necessary R files, data, and an answer document template.

  4. You do not need to create any new files or projects - everything will be set up for you in this personalised workspace.

Working in the Exam Environment

  1. All your work should be completed within the Posit Cloud environment. You will see an R Markdown file where you should input your answers.

  2. Required packages (fpp2, knitr, forecast, etc.) will be pre-installed in the workspace.

  3. Save your work frequently throughout the exam by clicking the “Save” button or using the keyboard shortcut (Ctrl+S or Cmd+S). This is crucial to prevent any loss of work.

  4. You can run code chunks and see outputs in real-time while working on your answers.

Submission Process

  1. You do not need to upload anything to Canvas after completing the exam.

  2. Your work is automatically saved in the Posit Cloud workspace as you progress.

  3. At the end of the examination period, the workspace will automatically close and your final saved version will be submitted.

  4. Ensure that all your work is saved at least 5 minutes before the end of the exam period to avoid any issues.

Important Notes

  • The workspace will only be accessible during the examination period and will close automatically when the exam time ends.
  • If you encounter any technical issues during the exam, notify the invigilator immediately.
  • Your work is private and cannot be viewed by other students.
  • All necessary data for the exam will be pre-loaded in the workspace.

Exam Structure

This exam is worth 50% of your final grade.
You will have two hours to answer a total of three questions. You must complete both questions in section 1 and choose one question from section 2.

Academic integrity pledge

By submitting your answers to this examination paper, you confirm that:

  1. You have completed the examination on your own;
  2. You did not collaborate with a third party or AI assistant during the examination;
  3. You did not use any other browser tabs, command line tools, or external resources during the examination;
  4. You understand that the lecturer and AI monitoring systems will be tracking browser activity and command line usage;
  5. You agree to complete an oral assessment if requested to do so.

Please note that plagiarism involves deliberately or inadvertently presenting someone else’s ideas as your own. It is cheating. It does not just apply to direct quotations but summarised and paraphrased arguments too. Plagiarism is treated very seriously and usually results in disciplinary action.

Read the README instructions

Before you begin

  1. Click on exam assignment to get your own copy.

  2. Make sure packages fpp2,knitr,forecast are loaded by running (.packages()) in console.

Section 1

Question 1

The following commodities series are avaliable in the forecast package; gold, woolyrnq and gas.

  1. Use an appropriate function to describe each series and write up your findings in your own words (10 marks)
Time Series:
Start = 1 
End = 1108 
Frequency = 1 
   [1] 306.25 299.50 303.45 296.75 304.40 298.35 304.00 304.00 301.25 302.50
  [11] 302.45 305.80 306.90 307.00 306.85 302.15 301.90 299.25 298.60 303.50
  [21] 303.00 304.90 304.80 301.25 301.75 303.45 302.50 300.60 300.00 303.45
  [31] 302.80 303.40 304.90 304.95 302.90 302.85 302.00 298.80 290.00 285.00
  [41] 290.75 290.50 288.10 288.30 288.85 286.70 289.30 289.00 290.25 288.75
  [51] 290.10 290.25 289.90 293.70 307.25 333.25 312.50 320.75 315.90 316.00
  [61] 329.90 328.75 329.80 324.65 317.00 321.10 317.00     NA     NA 323.10
  [71] 323.30 329.00 331.25 330.30 331.50 327.00 325.50 327.70 328.10 326.00
  [81] 322.60 322.40 322.50 323.00 324.65 315.60 314.25 313.70     NA 311.25
  [91] 313.35 314.50 313.55 316.75 324.75 322.85 320.40 319.80 323.65 316.50
 [101] 317.40 316.40 316.35     NA 313.90 311.20 315.00 313.15 316.85 316.25
 [111] 314.75 314.90 315.00 310.75 313.25 313.75 314.10 315.75 317.25 321.65
 [121] 325.20 322.00 315.25 314.10 315.90 316.50 316.25 316.50 313.35 310.85
 [131] 310.40 310.70 310.90 312.20 314.80 314.70 313.80 315.05 317.15 316.80
 [141] 321.70 322.25 319.00 317.40 322.75 318.50 319.40 317.60 323.00 323.25
 [151] 328.10 326.75 319.65 323.00 321.40 320.65 322.90 322.40 326.60 328.50
 [161] 326.20 328.90 335.40 339.25 335.50 335.75 337.60 333.60     NA 335.25
 [171] 339.30 338.40 335.75 335.45 332.70 325.00 326.00 318.75 320.20 320.00
 [181] 322.00 318.00 321.75 318.85 318.70 315.50 315.90 319.20 328.10 328.40
 [191] 328.70 330.40 328.95 326.50 323.15 324.75 324.35 330.55 326.25 326.10
 [201] 326.95 325.55 325.80 326.60 326.85 325.90 324.60 326.25 326.50 325.90
 [211] 326.90 325.95 325.65 326.50 326.55 326.80 325.75 324.65 325.60 324.55
 [221] 324.75 323.60 322.10 323.25 322.70 324.50 325.00 324.55 323.75 324.10
 [231] 325.05 325.75 326.00 330.50 331.50 330.45 326.75 327.40 323.95 322.50
 [241] 324.50 322.50 322.50 320.15 316.10 316.80 316.05 317.90 318.25 321.90
 [251] 321.10 323.40 323.55 325.75 324.85     NA     NA 324.80 326.15 327.00
 [261]     NA 327.10 326.00 327.80 328.90 330.90 333.90 339.45 340.75 338.80
 [271] 345.30 359.60 357.25 353.25 356.50 352.75 349.50 355.25 361.75 353.80
 [281] 354.40 355.40 354.00 347.35 338.50 335.95 337.10 337.90 340.50 337.20
 [291] 338.35 335.40 329.50 333.00 332.40 343.70 339.25 339.00 343.35 351.40
 [301] 345.10 337.85 338.25 339.45 337.90 342.20 343.00 342.00 341.80 341.65
 [311] 344.50 349.80 347.60 348.20 350.80 349.25 350.60 351.35 352.40 352.90
 [321] 344.90 345.50     NA     NA 333.70 335.50 336.60 335.60 336.50 340.65
 [331] 338.65 338.15 340.25 343.20 340.25 340.75 339.30 341.00 342.45 344.15
 [341] 347.25 346.00 344.30 344.40 342.35 344.75 345.60 341.60     NA 341.55
 [351] 342.15 344.60 344.25 344.90 343.80 342.75 342.50 342.75 342.05 340.30
 [361] 338.60 339.40 340.85     NA 341.15 341.60 342.75 343.35 343.00 341.85
 [371] 341.40 341.50 341.50 341.85 347.55 347.50 347.95 347.40 346.50 337.30
 [381] 338.50 338.70 338.90 340.50 340.75 343.25 343.80 343.55 345.50 345.65
 [391] 344.00 343.50 343.80 344.45 346.50 350.35 347.50 347.65 346.20 345.85
 [401] 348.35 346.90 347.10 353.00 353.50 351.75 348.50 349.00 350.80 353.30
 [411] 351.35 375.75 360.50 358.75 358.50 360.85 360.85 361.85 394.50 386.10
 [421] 391.25 384.00 386.40 377.25 372.50 379.00 381.75 384.65     NA 397.30
 [431] 377.80 384.00 386.00 392.00 395.50 407.20 404.00 418.25 419.00 412.50
 [441] 414.50 407.00 418.75 416.00 413.55 413.60 415.70 423.00 442.75 435.15
 [451] 434.00 432.25 434.00 429.45 421.20 425.50 425.50 436.90 436.50 442.00
 [461] 439.40 435.80 428.15 431.40 431.25 426.25 426.00 420.00 420.00 426.80
 [471] 426.60 425.40 413.00 409.60 409.55 407.75 404.00 401.50 400.30 408.50
 [481] 410.25 405.00 408.30 409.90 407.40 407.45 406.85 409.00 393.25 388.00
 [491] 391.50 387.00 389.50 380.40 380.75 384.00 382.30 390.00 399.60 394.30
 [501] 385.25 391.20 388.60 390.50 389.20 387.25 388.75 389.70 394.60 393.70
 [511] 393.40 392.50 394.15 395.35 392.75 391.00     NA     NA 391.40 389.40
 [521] 390.90     NA 402.40 399.00 401.70 399.50 401.60 402.25 409.90 408.60
 [531] 414.40 415.00 414.50 421.25 417.40 408.50 410.60 403.55 403.35 408.70
 [541] 416.50 411.00 407.30 406.45 402.00 401.75 402.60 402.70 402.95 404.40
 [551] 402.90 402.00 395.55 397.20 396.85 392.25 392.60 397.50 403.00 401.95
 [561] 406.70 403.10 408.70 404.40 403.70 407.65 411.45 406.50 404.85 405.00
 [571] 406.85 408.00 409.25 404.65 406.00 406.40 405.05 405.00 406.60 410.30
 [581] 415.00 411.30 415.90 421.80 419.00 418.50 420.25 418.65 420.55 419.80
 [591] 423.20 421.50 423.30 436.50 440.25 445.50 441.00     NA     NA 454.30
 [601] 446.80 453.00 462.60 476.60 455.75 451.75 454.50 452.15     NA 464.50
 [611] 456.75 457.40 456.70 454.75 460.25 459.50 460.00 466.70 476.50 471.35
 [621] 479.95 468.60 473.60     NA 459.65 447.90 453.35 451.75 443.40 449.30
 [631] 453.35 450.25 454.70 454.40 452.05 456.65 456.40 460.80 450.35 452.75
 [641] 448.25 451.10 452.25 443.60 438.10 443.00 439.00 441.40 446.00 447.10
 [651] 449.50 447.40 443.00 443.10 444.80 442.15 445.30 444.25 443.70 447.15
 [661] 448.25 452.90 452.50 449.65 452.50 454.45 454.75 454.00 453.10 454.20
 [671] 459.50 457.20 464.20 473.25 476.00 469.85 468.85 464.00 459.50 463.20
 [681] 461.00 462.00 457.40 454.80 454.90 457.65 457.40 454.10 455.80 458.50
 [691] 457.40 458.25 455.90     NA 453.10 456.55 462.15 464.40 463.35 462.75
 [701] 458.00 461.00 460.90 456.60 458.35 458.50 458.80 461.35 458.85 463.15
 [711] 461.05 463.85 461.00 460.90 458.90 459.15 454.10 455.00 455.15 456.85
 [721] 458.55 458.25 461.75 461.85 459.65 459.45 461.75 464.25 479.50 481.60
 [731] 466.65 469.80 472.65 474.85 473.45 479.65 474.05 468.00 469.95 470.10
 [741] 467.00 459.70 458.60 463.50 458.75 461.30 463.00 464.20 461.75 463.55
 [751] 464.20 465.80 466.25 468.25 476.95 478.75 477.65 477.80 493.90 486.90
 [761] 490.00 488.95 485.75 480.90 483.00 485.30 484.50 495.00 502.75 593.70
 [771] 487.05 487.75 484.55 481.00 481.60 483.25 483.75     NA     NA 489.55
 [781] 486.90 486.50     NA 484.10 477.30 481.60 483.95 479.50 485.30 482.05
 [791] 481.40 480.90 484.80 475.85 476.75 477.75 476.50 477.85 471.40 471.40
 [801] 469.40 468.00 465.25 454.65 455.15 447.10 437.60 444.15 443.05 439.25
 [811] 443.80 440.20 440.30 443.60 444.25 444.40 446.25 443.45 445.10 443.95
 [821] 438.00 433.95 432.65 423.75 429.15 431.55 429.15 430.75 436.00 435.70
 [831] 436.10 437.25 444.10 441.90 442.25 447.15 445.35 442.80 446.50 449.40
 [841] 450.00 453.90 451.50 453.10 454.70 454.00 458.00     NA     NA 456.00
 [851] 450.80 446.25 448.60 450.15 450.20 448.50 447.00 453.85 457.55 456.55
 [861] 458.00 454.00 453.15 449.75 448.25 449.10 452.15 449.75     NA 444.30
 [871] 441.95 445.35 445.95 443.60 447.10 449.35 448.65 451.05 453.40 453.15
 [881] 452.70 456.65 459.50 460.25 458.60 458.60 453.00 452.50     NA 454.00
 [891] 457.00 454.60 464.85 464.10 463.40 458.75 455.00 457.10 450.50 450.80
 [901] 450.30 452.65 449.80 453.90 451.70 449.80 447.60 447.00 442.00 443.85
 [911] 434.90 436.85 436.50 437.15 437.40 438.10 439.15 438.90 439.65 434.50
 [921] 436.20 439.05 438.10 437.65 437.25 445.00 443.20 443.20 442.20 430.15
 [931] 431.70 428.75 432.70 436.40 432.90 431.25 433.40 431.45 431.85 428.25
 [941] 426.95 429.00 428.40 431.15 432.00 429.00 430.20 432.40 429.70 432.70
 [951] 432.10 434.80 433.75     NA 429.40 426.35 430.30 430.30 427.00 427.65
 [961] 427.00 428.00 428.90 418.00 420.80 421.90 421.50 417.30 409.00 410.40
 [971] 401.60 399.60 399.30 389.05 397.00 397.65 398.60 396.15 394.20 397.35
 [981] 397.25 403.00 404.25 406.25 408.00 404.70 408.60 406.50 411.15 413.05
 [991] 410.80 411.40 410.55 406.30 406.60 407.50 407.15 407.30 412.30 411.00
[1001] 412.50 422.90 419.50 422.00 421.85 419.50 422.25 420.75 420.65 422.80
[1011] 422.60 423.30 419.75 416.60 416.10 417.95 419.85 422.60 421.40 422.10
[1021] 421.30 425.50 423.80 430.40 429.00 425.35 423.30 422.20 421.00 420.05
[1031] 419.60 421.40 412.60 413.65 413.20 413.85 415.60 417.55     NA     NA
[1041] 413.65 413.10 410.15     NA 413.60 410.50 408.00 408.45 404.45 405.50
[1051] 403.50 404.85 403.50 401.75 402.10 402.85 402.30 404.50 407.75 407.80
[1061] 404.75 406.00 402.25 394.30 394.85 392.00 392.70 390.85 390.25 391.45
[1071] 390.40 394.10 393.80 386.70 385.65 381.70 384.25 378.95 382.15 382.75
[1081] 386.00 389.00 389.25 390.75 386.75 386.10 384.10 384.10 388.40 386.30
[1091] 393.10 392.50 397.00 393.10 394.30 394.45 391.00 389.25 395.30 394.10
[1101] 393.40 396.00     NA     NA 391.25 383.30 384.00 382.30
  1. Plot each of these in separate plots in a professional manner. Describe what you see in your own words. (10 marks)
  1. What is the frequency of each commodity series? (5 marks)
  1. Check each series for outliers. Which observations in which series do you suspect is an outlier? Briefly explain your answer. (15 marks)

Question 2

Use the appropriate time series graphics functions to explore features from the following time series: hsales, usdeaths, bricksq, sunspotarea, gasoline.

For each time series describe (using text below each R code chunk) the salient features of the data that an ethical econometrician should consider (50 marks)

Section 2

Question 3

We will use the bricksq data (Australian quarterly clay brick production) for this exercise.

  1. Use an STL decomposition to calculate the trend-cycle and seasonal indices. Briefly discuss your results (10 Marks) use help(stl) to research this function.
help(stl)

You should experiment with having fixed or changing seasonality. There’s some change in variation, and BoxCox.lambda(bricksq) gives a value of 0.25.

  1. Compute and plot the seasonally adjusted data. (5 marks)
  1. Use a naive method to produce forecasts of the seasonally adjusted data. (5 marks)
  1. Use the stlf function to reseasonalize the results, giving forecasts for the original data. (10 marks)
  1. Do the residuals look uncorrelated? Provide statistical evidence and discuss your results (5 marks)

Comment on the results here

  1. Repeat with a robust STL decomposition (using argument robust=TRUE). Does it make much difference? (5 marks)

Comment on the results here

  1. Compare forecasts from stlf with those from snaive, using a test set comprising the last 2 years of data. Which would you use as a professional forecaster? Explain your answer. (10 marks)

Comment on the results here

Question 4

  1. Plot the annual bituminous coal production in the United States from 1920 to 1968 (data set bicoal). Describe what you see (10 marks)

Comment on the results here

  1. You decide to fit the following model to the series: \[y_t = c + \phi_1 y_{t-1} + \phi_2 y_{t-2} + \phi_3 y_{t-3} + \phi_4 y_{t-4} + e_t\] where \(y_t\) is the coal production in year \(t\) and \(e_t\) is a white noise series. What sort of ARIMA model is this (i.e., what are \(p\), \(d\), and \(q\))? (5 marks)
  1. Explain why this model was chosen using the ACF and PACF. (10 marks)

Comment on the results here

  1. The last five values of the series are given below.
Year 1964 1965 1966 1967 1968
Millions of tons 467 512 534 552 545

The estimated parameters are \(c = 162.00\), \(\phi_1 = 0.83\), \(\phi_2 = -0.34\), \(\phi_3 = 0.55\), and \(\phi_4 = -0.38\).

Without using the forecast function, calculate forecasts for the next three years (1969–1971). (15 marks)

  1. Now fit the model in R and obtain the forecasts from the same model. How are they different from yours? Why? (10 marks)

Question 5

In your own words write a reflective essay on your experience collaborating with Large Language Models for your analytics project? (35 marks)

What are the benefits and limitations of such an approach? (15 marks)